Applying lean six sigma incorporated with big data analysis to curriculum system improvement in higher education institutions

2021 ◽  
Author(s):  
Shang Shanshan ◽  
Lyv Wenfei ◽  
Luo Lijuan
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
Six Sigma ◽  
Higher Education Institutions ◽  
Big Data Analysis ◽  
Lean Six Sigma ◽  
System Improvement

scholarly journals A News Big Data Analysis of Issues in Higher Education in Korea amid the COVID-19 Pandemic

2021 ◽  
Vol 13 (13) ◽  
pp. 7347
Author(s):  
Jangwan Ko ◽  
Seungsu Paek ◽  
Seoyoon Park ◽  
Jiwoo Park
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
College Education ◽  
Big Data Analysis ◽  
Second Phase ◽  
Public Attention ◽  
Job Market ◽  
Media Reports ◽  
The Government

This paper examines the main issues regarding higher education in Korea—where college education experienced minimal interruptions—during the COVID-19 pandemic through a big data analysis of news articles. By analyzing policy responses from the government and colleges and examining prominent discourses on higher education, it provides a context for discussing the implications of COVID-19 on education policy and what the post-pandemic era would bring. To this end, we utilized BIgKinds, a big data research solution for news articles offered by the Korea Press Foundation, to select a total of 2636 media reports and conducted Topic Modelling based on LDA algorithms using NetMiner. The analyses are split into three distinct periods of COVID-19 spread in the country. Some notable topics from the first phase are remote class, tuition refund, returning Chinese international students, and normalization of college education. Preparations for the College Scholastic Ability Test (CSAT), contact and contactless classes, preparations for early admissions, and supporting job market candidates are extracted for the second phase. For the third phase, the extracted topics include CSAT and college-specific exams, quarantine on campus, social relations on campus, and support for job market candidates. The results confirmed widespread public attention to the relevant issues but also showed empirically that the measures taken by the government and college administrations to combat COVID-19 had limited visibility among media reports. It is important to note that timely and appropriate responses from the government and colleges have enabled continuation of higher education in some capacity during the pandemic. In addition to the media’s role in reporting issues of public interest, there is also a need for continued research and discussion on higher education amid COVID-19 to help effect actual results from various policy efforts.

Lean Six Sigma Leadership in Higher Education Institutions

2020 ◽  
pp. 129-137
Author(s):  
Jing Lu ◽  
Arush Saxena ◽  
Chad Laux ◽  
Jenny Daugherty ◽  
Lin Qian
Keyword(s):  
Higher Education ◽  
Six Sigma ◽  
Higher Education Institutions ◽  
Lean Six Sigma ◽  
Leadership In Higher Education

Lean Six Sigma leadership in higher education institutions

2017 ◽  
Vol 66 (5) ◽  
pp. 638-650 ◽  
Author(s):  
Jing Lu ◽  
Chad Laux ◽  
Jiju Antony
Keyword(s):  
Higher Education ◽  
Six Sigma ◽  
Higher Education Institutions ◽  
Lean Six Sigma ◽  
Quality Of Education ◽  
Leadership Model ◽  
Content Type ◽  
Wide Range ◽  
Leadership Framework

Purpose The purpose of this paper is to critically evaluate whether a Lean Six Sigma (LSS) leadership model could be effectively utilized to resolve efficiency and effective issues like rising costs, quality of education, graduation and retention rates encountered in higher education institutions (HEIs) in the modern era. Design/methodology/approach The authors systematically reviewed the literature on key concepts of LSS and leadership in HEIs in to develop a theoretical model using an inductive theory-building approach in accordance with the exploratory nature of the study. Findings The results of the study proposed a conceptual LSS leadership framework, which provides a basis for testing of LSS leadership representations in HEIs. The results suggest that LSS leadership has advantages for HEI to overcome currents issues and challenges. Research limitations/implications This research is a theoretical study based on the existing literature that identified characteristics that may be adopted in higher education. The proposed LSS leadership framework is based upon leadership, statistical thinking, continuous change and improvement. This model is based upon service and the concepts of adaptive, rather than technical work, of leaders in higher education. Practical implications The proposed LSS leadership framework brings new aspects and perspectives of leadership in HEIs. LSS leadership model has its practical meaning in providing a fundamental base for HEIs to overcome challenges, fulfill missions, and sustain improvements. Social implications HEIs are a foundation for principles of democracy, equality and diversity. HEIs have been a path for citizens but HEIs are facing challenges that are reducing the ability of individuals to improve themselves. Leadership of HEI needs to incorporate new principles to adapt to a changing society. Originality/value LSS project leaders have achieved improved bottom line results and customer satisfaction in a wide range of industries, but LSS application in the HEIs remains to be explored. This paper proposes an effective LSS leadership model, which can help improve the quality of education, reduce non-value added costs and enhance operational efficiency of HEIs.

scholarly journals Implementasi Big Data Analytical Untuk Perguruan Tinggi Menggunakan Machine Learning

2021 ◽  
Vol 2 (1) ◽  
pp. 77-88
Author(s):  
Rakhmat Purnomo ◽  
Wowon Priatna ◽  
Tri Dharma Putra
Keyword(s):  
Higher Education ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Student Performance ◽  
Big Data Analytics ◽  
Big Data Analysis ◽  
Process Data ◽  
Grouping Students

The dynamics of higher education are changing and emphasize the need to adapt quickly. Higher education is under the supervision of accreditation agencies, governments and other stakeholders to seek new ways to improve and monitor student success and other institutional policies. Many agencies fail to make efficient use of the large amounts of available data. With the use of big data analytics in higher education, it can be obtained more insight into students, academics, and the process in higher education so that it supports predictive analysis and improves decision making. The purpose of this research is to implement big data analytical to increase the decision making of the competent party. This research begins with the identification of process data based on analytical learning, academic and process in the campus environment. The data used in this study is a public dataset from UCI machine learning, from the 33 available varibales, 4 varibales are used to measure student performance. Big data analysis in this study uses spark apace as a library to operate pyspark so that python can process big data analysis. The data already in the master slave is grouped using k-mean clustering to get the best performing student group. The results of this study succeeded in grouping students into 5 clusters, cluster 1 including the best student performance and cluster 5 including the lowest student performance

A conceptual Lean Six Sigma framework for quality excellence in higher education institutions

2018 ◽  
Vol 35 (4) ◽  
pp. 857-874 ◽  
Author(s):  
Vijaya Sunder M. ◽  
Jiju Antony
Keyword(s):  
Higher Education ◽  
Conceptual Framework ◽  
Six Sigma ◽  
Manufacturing Sector ◽  
Higher Education Institutions ◽  
Real Life ◽  
Lean Six Sigma ◽  
Content Type ◽  
Deployment Strategy ◽  
Life Context

Purpose The purpose of this paper is to present the potent application of Lean Six Sigma (LSS) in higher education services and to suggest a conceptual framework of deploying LSS in the higher education institutions (HEIs). Design/methodology/approach This paper aims to outline the importance of the quality excellence criterion in general through different constructs from the literature including TQM, Lean, Six Sigma and LSS. The paper further expands on the applicability of LSS in the HEI setting, with an understanding of HEI as comparatively different from the manufacturing sector from where LSS originated. The published literature on LSS and authors’ experience in the field of LSS (as practitioners) were used as sources for devising a conceptual framework for LSS deployment in HEIs. Findings The key finding from the study is the confirmation of LSS applicability in HEIs. The study also confirms that LSS is not anyone’s job but a key part of leadership agenda. The six-staged conceptual framework prescribed for the HEIs as part of the paper is the key contribution of this study. The model describes that LSS readiness is the foremost step in the LSS deployment journey in HEIs. The strategic perspectives of aligning the organisational vision for quality excellence need to be achieved by establishing a need for LSS through leadership. Then, developing an LSS deployment strategy becomes the next step. Educating the appropriate stakeholders (students) and team formation becomes the next important steps in the LSS deployment. Once the above steps are implemented in right way, identifying and implementing LSS projects becomes critical. The execution and closure of the LSS projects leads to quality excellence in HEIs. Research limitations/implications Since the framework prescribed here is a conceptual framework, it deserved a testing in the real-life context. This leaves an opportunity for future researchers to test and expand on the implications of the model. Though the LSS framework is customised for HEIs, the fundamental factors essential for any change management initiative holds correct for LSS as well, and hence these are not elaborated as part of this paper. Originality/value This paper would serve as an excellent resource for both academicians and LSS practitioners in HEIs, for deployment. The framework presented here is the original work contributed by the authors, as the first of its kind in the academic literature relevant to LSS in HEIs.

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